Source: datascience: An online community for showcasing R & Python tutorials. It operates as a networking platform for data scientists to promote their talent and get hired. Our mission is to empower data scientists by bridging the gap between talent and opportunity.

GitHub repository (source: https://rstudio.github.io/shiny/tutorial/#deployment-local)
If your project is stored in a git repository on GitHub, then others can download and run your app directly. An example repository is at https://github.com/rstudio/shiny_example. The following command will download and run the application:

shiny::runGitHub('shiny_example', 'rstudio')
In this example, the GitHub account is ‘rstudio’ and the repository is ‘shiny_example’; you will need to replace them with your account and repository name.

Pros
Source code is easily visible by recipient (if desired)
Easy to run (for R users)
Very easy to update if you already use GitHub for your project
Git-savvy users can clone and fork your repository
Cons
Developer must know how to use git and GitHub
Code is hosted by a third-party server

Welcome to MySci -page. Here I introduce some innovative and most interesting things about my trip into doctoral carreer. Now Im doctoral student in LUt and I wonder every day how amazing things you could do nowadays with your laptop. Data mining, AI and IoT will be in some role in my SciBlog. So… if you dare, just follow these pages!